Using genomics data to reconstruct transmission trees during disease outbreaks.

Genetic sequence data from pathogens present a novel means to investigate the spread of infectious disease between infected hosts or infected premises, complementing traditional contact-tracing approaches, and much recent work has gone into developing methods for this purpose. The objective is to recover the epidemic transmission tree, which identifies who infected whom. This paper reviews the various approaches that have been taken. The first step is to define a measure of difference between sequences, which must be done while taking into account such factors as recombination and convergent evolution. Three broad categories of method exist, of increasing complexity: those that assume no withinhost genetic diversity or mutation, those that assume no within-host diversity but allow mutation, and those that allow both. Until recently, the assumption was usually made that every host in the epidemic could be identified, but this is now being relaxed, and some methods are intended for sparsely sampled data, concentrating on the identification of pairs of sequences that are likely to be the result of direct transmission rather than inferring the complete transmission tree. Many of the procedures described here are available to researchers as free software.

L'accès aux données sur les séquences génétiques des agents pathogènes ouvre de nouvelles perspectives pour étudier la manière dont les maladies infectieuses se propagent entre différents hôtes ou établissements infectés, en complément des méthodes traditionnelles d'évaluation de l'exposition ; de grands efforts ont donc été déployés pour mettre au point des techniques permettant d'arriver à cette fin. Leur objectif est de reconstituer l'arborescence de la transmission d'une épidémie, ce qui permet d'identifier chaque individu ayant infecté d'autres individus. Les auteurs passent en revue les différentes méthodes appliquées. La première étape consiste à définir les modalités de mesure des différences entre séquences, ainsi que les facteurs à prendre en compte, par exemple les phénomènes de recombinaison ou d'évolution convergente. Les méthodes disponibles se répartissent en trois catégories principales, par ordre de complexité croissante : celles qui présupposent qu'il ne peut y avoir de diversité ni de mutation génétiques chez l'hôte ; celles qui présupposent qu'il peut y avoir une diversité génétique mais pas de mutation ; enfin celles qui présupposent qu'il peut y avoir les deux. Jusqu'à une période récente, le présupposé le plus courant était que tous les hôtes intervenant dans un foyer pouvaient être identifiés ; cette exigence s'est considérablement assouplie et de nouvelles méthodes ont été conçues pour travailler à partir d'un échantillon de données plus clairsemé, ce qui permet de se concentrer sur l'identification de paires de séquences révélatrices d'une transmission directe au lieu de déduire l'intégralité de l'arbre de transmission. La plupart des procédures décrites par les auteurs existent sous forme de logiciels libres accessibles aux chercheurs.

Los datos de la secuencia genética de patógenos ofrecen un medio novedoso para investigar la propagación de enfermedades infecciosas entre individuos o establecimientos infectados, medio que viene a complementar la fórmula tradicional consistente en rastrear los contactos. De ahí que últimamente se haya dedicado un ingente trabajo a definir métodos útiles para ese fin. El objetivo radica en desentrañar el árbol de transmisión epidémica, que permite determinar quién infectó a quién. Los autores pasan revista a los diferentes planteamientos adoptados. El primer paso consiste en definir una medida de la diferencia entre secuencias, para lo cual hay que tener en cuenta factores como la recombinación o la convergencia evolutiva. Existen tres grandes clases de métodos, que presentan un grado creciente de complejidad: aquellos que presuponen que no hay diversidad genética ni mutaciones dentro del individuo infectado; aquellos que presuponen que no hay diversidad, pero admiten la posibilidad de mutaciones; y aquellos que postulan que ambas cosas pueden producirse. Hasta hace poco, en general se partía de la premisa de que era posible identificar a todos los individuos infectados en una epidemia. Ahora, sin embargo, se está flexibilizando este postulado, y existen métodos que se aplican específicamente a datos obtenidos con muestreos dispersos, con los cuales se trata de determinar pares de secuencias que probablemente sean resultado de la transmisión directa, y no tanto de inferir el árbol de transmisión completo. Muchos de los procedimientos aquí descritos están a disposición de los investigadores en forma de programas informáticos gratuitos.

Fold or hold: experimental evolution in vitro.

We introduce a system for experimental evolution consisting of populations of short oligonucleotides (Oli populations) evolving in a modified quantitative polymerase chain reaction (qPCR). It is tractable at the genetic, genomic, phenotypic and fitness levels. The Oli system uses DNA hairpins designed to form structures that self-prime under defined conditions. Selection acts on the phenotype of self-priming, after which differences in fitness are amplified and quantified using qPCR. We outline the methodological and bioinformatics tools for the Oli system here and demonstrate that it can be used as a conventional experimental evolution model system by test-driving it in an experiment investigating adaptive evolution under different rates of environmental change.

Real-time characterization of the molecular epidemiology of an influenza pandemic.

Early characterization of the epidemiology and evolution of a pandemic is essential for determining the most appropriate interventions. During the 2009 H1N1 influenza A pandemic, public databases facilitated widespread sharing of genetic sequence data from the outset. We use Bayesian phylogenetics to simulate real-time estimates of the evolutionary rate, date of emergence and intrinsic growth rate (r0) of the pandemic from whole-genome sequences. We investigate the effects of temporal range of sampling and dataset size on the precision and accuracy of parameter estimation. Parameters can be accurately estimated as early as two months after the first reported case, from 100 genomes and the choice of growth model is important for accurate estimation of r0. This demonstrates the utility of simple coalescent models to rapidly inform intervention strategies during a pandemic.

Estimation of an in vivo fitness landscape experienced by HIV-1 under drug selective pressure useful for prediction of drug resistance evolution during treatment.

MOTIVATION: HIV-1 antiviral resistance is a major cause of antiviral treatment failure. The in vivo fitness landscape experienced by the virus in presence of treatment could in principle be used to determine both the susceptibility of the virus to the treatment and the genetic barrier to resistance. We propose a method to estimate this fitness landscape from cross-sectional clinical genetic sequence data of different subtypes, by reverse engineering the required selective pressure for HIV-1 sequences obtained from treatment naive patients, to evolve towards sequences obtained from treated patients. The method was evaluated for recovering 10 random fictive selective pressures in simulation experiments, and for modeling the selective pressure under treatment with the protease inhibitor nelfinavir. RESULTS: The estimated fitness function under nelfinavir treatment considered fitness contributions of 114 mutations at 48 sites. Estimated fitness correlated significantly with the in vitro resistance phenotype in 519 matched genotype-phenotype pairs (R(2) = 0.47 (0.41 - 0.54)) and variation in predicted evolution under nelfinavir selective pressure correlated significantly with observed in vivo evolution during nelfinavir treatment for 39 mutations (with FDR = 0.05). AVAILABILITY: The software is available on request from the authors, and data sets are available from http://jose.med.kuleuven.be/~kdforc0/nfv-fitness-data/.

The evolutionary dynamics of canid and mongoose rabies virus in Southern Africa.

Two variants of rabies virus (RABV) currently circulate in southern Africa: canid RABV, mainly associated with dogs, jackals, and bat-eared foxes, and mongoose RABV. To investigate the evolutionary dynamics of these variants, we performed coalescent-based analyses of the G-L inter-genic region, allowing for rate variation among viral lineages through the use of a relaxed molecular clock. This revealed that mongoose RABV is evolving more slowly than canid RABV, with mean evolutionary rates of 0.826 and 1.676 x 10(-3) nucleotide substitutions per site, per year, respectively. Additionally, mongoose RABV exhibits older genetic diversity than canid RABV, with common ancestors dating to 73 and 30 years, respectively, and while mongoose RABV has experienced exponential population growth over its evolutionary history in Africa, populations of canid RABV have maintained a constant size. Hence, despite circulating in the same geographic region, these two variants of RABV exhibit striking differences in evolutionary dynamics which are likely to reflect differences in their underlying ecology.

Bayesian coalescent inference of past population dynamics from molecular sequences.

We introduce the Bayesian skyline plot, a new method for estimating past population dynamics through time from a sample of molecular sequences without dependence on a prespecified parametric model of demographic history. We describe a Markov chain Monte Carlo sampling procedure that efficiently samples a variant of the generalized skyline plot, given sequence data, and combines these plots to generate a posterior distribution of effective population size through time. We apply the Bayesian skyline plot to simulated data sets and show that it correctly reconstructs demographic history under canonical scenarios. Finally, we compare the Bayesian skyline plot model to previous coalescent approaches by analyzing two real data sets (hepatitis C virus in Egypt and mitochondrial DNA of Beringian bison) that have been previously investigated using alternative coalescent methods. In the bison analysis, we detect a severe but previously unrecognized bottleneck, estimated to have occurred 10,000 radiocarbon years ago, which coincides with both the earliest undisputed record of large numbers of humans in Alaska and the megafaunal extinctions in North America at the beginning of the Holocene.

The epidemiology and iatrogenic transmission of hepatitis C virus in Egypt: a Bayesian coalescent approach.

Hepatitis C virus (HCV) is a leading cause of liver cancer and cirrhosis, and Egypt has possibly the highest HCV prevalence worldwide. In this article we use a newly developed Bayesian inference framework to estimate the transmission dynamics of HCV in Egypt from sampled viral gene sequences, and to predict the public health impact of the virus. Our results indicate that the effective number of HCV infections in Egypt underwent rapid exponential growth between 1930 and 1955. The timing and speed of this spread provides quantitative genetic evidence that the Egyptian HCV epidemic was initiated and propagated by extensive antischistosomiasis injection campaigns. Although our results show that HCV transmission has since decreased, we conclude that HCV is likely to remain prevalent in Egypt for several decades. Our combined population genetic and epidemiological analysis provides detailed estimates of historical changes in Egyptian HCV prevalence. Because our results are consistent with a demographic scenario specified a priori, they also provide an objective test of inference methods based on the coalescent process.

GENIE: estimating demographic history from molecular phylogenies.

UNLABELLED: GENIE implements a statistical framework for inferring the demographic history of a population from phylogenies that have been reconstructed from sampled DNA sequences. The methods are based on population genetic models known collectively as coalescent theory. AVAILABILITY: GENIE is available from http://evolve.zoo.ox.ac.uk. All popular operating systems are supported.

New inferences from tree shape: numbers of missing taxa and population growth rates.

The relative positions of branching events in a phylogeny contain information about evolutionary and population dynamic processes. We provide new summary statistics of branching event times and describe how these statistics can be used to infer rates of species diversification from interspecies trees or rates of population growth from intraspecies trees. We also introduce a phylogenetic method for estimating the level of taxon sampling in a clade. Different evolutionary models and different sampling regimes can produce similar patterns of branching events, so it is important to consider explicitly the model assumptions involved when making evolutionary inferences. Results of an analysis of the phylogeny of the mosquito-borne flaviviruses suggest that there could be several thousand currently unidentified viruses in this clade.

The epidemic behavior of the hepatitis C virus.

Hepatitis C virus (HCV) is a leading worldwide cause of liver disease. Here, we use a new model of HCV spread to investigate the epidemic behavior of the virus and to estimate its basic reproductive number from gene sequence data. We find significant differences in epidemic behavior among HCV subtypes and suggest that these differences are largely the result of subtype-specific transmission patterns. Our model builds a bridge between the disciplines of population genetics and mathematical epidemiology by using pathogen gene sequences to infer the population dynamic history of an infectious disease.

Complete mitochondrial genome sequences of two extinct moas clarify ratite evolution.

The origin of the ratites, large flightless birds from the Southern Hemisphere, along with their flighted sister taxa, the South American tinamous, is central to understanding the role of plate tectonics in the distributions of modern birds and mammals. Defining the dates of ratite divergences is also critical for determining the age of modern avian orders. To resolve the ratite phylogeny and provide biogeographical data to examine these issues, we have here determined the first complete mitochondrial genome sequences of any extinct taxa--two New Zealand moa genera--along with a 1,000-base-pair sequence from an extinct Madagascan elephant-bird. For comparative data, we also generated 12 kilobases of contiguous sequence from the kiwi, cassowary, emu and two tinamou genera. This large dataset allows statistically precise estimates of molecular divergence dates and these support a Late Cretaceous vicariant speciation of ratite taxa, followed by the subsequent dispersal of the kiwi to New Zealand. This first molecular view of the break-up of Gondwana provides a new temporal framework for speciation events within other Gondwanan biota and can be used to evaluate competing biogeographical hypotheses.

Evolutionary rate differences in trypanosomes.

Ribosomal RNA-based studies of trypanosome phylogenies have highlighted considerable differences in genetic diversity within clades in the genus Trypanosoma and several-fold substitution rate differences between clades have been identified. While early 18S rRNA-based studies were hampered by highly variable substitution rates and long-branch attraction, it is apparent that genuine differences in evolution rates within localized clades do exist and questions remain regarding what rate or rates such clades are evolving at and why is the application of a single clock to trypanosome evolution so inappropriate? In this study, we explore rate heterogeneity in the commonly used 18S rRNA gene across genus Trypanosoma, using a maximum likelihood (ML) approach to explore local rate variations in clades of biological interest.

Comparative analyses for adaptive radiations.

Biologists generally agree that most morphological variation between closely related species is adaptive. The most common method of comparative analysis to test for co-evolved character variation is based on a Brownian-motion model of character evolution. If we are to test for the evolution of character-covariation, and we believe that characters have evolved adaptively to fill niches during an adaptive radiation, then it is appropriate to employ appropriate models for character evolution. We show here that under several models of adaptive character evolution and coevolution during an adaptive radiation, which result in closely related species being more similar to each other than to more distantly related species, cross-species analyses are statistically more appropriate than contrast analyses. If the evolution of some traits fits the Brownian-motion model, while others evolve to fill niches during an adaptive radiation, it might be necessary to identify the number of relevant niche dimensions and the modes of character evolution before deciding on appropriate statistical procedures. Alternatively, maximum-likelihood procedures might be used to determine appropriate transformations of phylogenetic branch lengths that accord with particular models of character evolution.

An integrated framework for the inference of viral population history from reconstructed genealogies.

We describe a unified set of methods for the inference of demographic history using genealogies reconstructed from gene sequence data. We introduce the skyline plot, a graphical, nonparametric estimate of demographic history. We discuss both maximum-likelihood parameter estimation and demographic hypothesis testing. Simulations are carried out to investigate the statistical properties of maximum-likelihood estimates of demographic parameters. The simulations reveal that (i) the performance of exponential growth model estimates is determined by a simple function of the true parameter values and (ii) under some conditions, estimates from reconstructed trees perform as well as estimates from perfect trees. We apply our methods to HIV-1 sequence data and find strong evidence that subtypes A and B have different demographic histories. We also provide the first (albeit tentative) genetic evidence for a recent decrease in the growth rate of subtype B.

Estimating the rate of molecular evolution: incorporating non-contemporaneous sequences into maximum likelihood phylogenies.

MOTIVATION: TipDate is a program that will use sequences that have been isolated at different dates to estimate their rate of molecular evolution. The program provides a maximum likelihood estimate of the rate and also the associated date of the most recent common ancestor of the sequences, under a model which assumes a constant rate of substitution (molecular clock) but which accommodates the dates of isolation. Confidence intervals for these parameters are also estimated. RESULTS: The approach was applied to a sample of 17 dengue virus serotype 4 sequences, isolated at dates ranging from 1956 to 1994. The rate of substitution for this serotype was estimated to be 7.91 x 10(-4) substitutions per site per year (95% confidence intervals of 6.07 x 10(-4), 9.86 x 10(-4)). This is compatible with a date of 1922 (95% confidence intervals of 1900-1936) for the most recent common ancestor of these sequences. AVAILABILITY: TipDate can be obtained by WWW from http://evolve.zoo. ox.ac.uk/software. The package includes the source code, manual and example files. Both UNIX and Apple Macintosh versions are available from the same site.

Testing the extent of sequence similarity among viroids, satellite RNAs, and hepatitis delta virus.

A Monte Carlo method was used to test the extent of sequence similarity among viroids, satellite RNAs, and hepatitis delta virus. This analysis revealed that there is insufficient sequence similarity among these pathogens to support the hypothesis that they have a common evolutionary origin. Furthermore, while definite patterns of sequence similarity were observed among some viroids, there was a clear lack of overall similarity, indicating that a monophyletic origin for even this group cannot be reliably supported from sequence data alone.

The power of relative rates tests depends on the data.

One of the most useful features of molecular phylogenetic analyses is the potential for estimating dates of divergence of evolutionary lineages from the DNA of extant species. But lineage-specific variation in rate of molecular evolution complicates molecular dating, because a calibration rate estimated from one lineage may not be an accurate representation of the rate in other lineages. Many molecular dating studies use a "clock test" to identify and exclude sequences that vary in rate between lineages. However, these clock tests should not be relied upon without a critical examination of their effectiveness at removing rate variable sequences from any given data set, particularly with regard to the sequence length and number of variable sites. As an illustration of this problem we present a power test of a frequently employed triplet relative rates test. We conclude that (1) relative rates tests are unlikely to detect moderate levels of lineage-specific rate variation (where one lineage has a rate of molecular evolution 1.5 to 4.0 times the other) for most commonly used sequences in molecular dating analyses, and (2) this lack of power is likely to result in substantial error in the estimation of dates of divergence. As an example, we show that the well-studied rate difference between murid rodents and great apes will not be detected for many of the sequences used to date the divergence between these two lineages and that this failure to detect rate variation is likely to result in consistent overestimation the date of the rodent-primate split.